This invention relates to computed tomography (CT) and more particularly to a method and apparatus for removing artifacts from CT images caused by the presence of multiple high density structures in the object region being imaged.
Modern computed tomography has provided diagnostic images containing information which was either not available or difficult to interpret using prior imaging techniques. At the same time, structures in or on the body which had previously not created serious imaging problems have led to artifacts which made CT images difficult to interpret.
One example of such structures is that of surgical clips present within the slice to be imaged. Other examples include dental fillings, contrast materials, and prostheses. Such objects are typically of very high density as compared to the surrounding tissue and are often found to create artifacts known as "starburst." Such artifacts limit the diagnostic utility of the CT image. It is therefore desirable to provide a method for eliminating or reducing such artifacts.
The general basis for many artifact removal methods which rely on modification of projection data to produce a corrected image is the assumption that the detector readings corresponding to the line integrals (which comprise the projection measurements) through a high-density object(s) are invalid and, hence, cannot be used in the reconstruction algorithm. This method of artifact correction, in effect, removes the high-density object because the projection data corresponding to the object is removed prior to reconstruction of a corrected image. Such methods are to be distinguished from techniques such as that disclosed in U.S. Pat. No. 4,075,700 in which image features which are not of interest are removed by operating on image data which is derivable only after processing the projection measurements. In accordance with the technique disclosed in the aforeidentified patent, the position coordinates of the features to be removed are identified, and the corresponding absorption coefficients are assigned zero or maximum values, thereby erasing features of little interest. Techniques of this kind have been found ineffective in removing artifacts due to the presence of high density objects in the field of view, primarily for the reason that the operation is cosmetic and does not correct the underlying errors in the projection data.
In accordance with the artifact removal methods relying on the correction of the projection data, itself, rather than modification of image data, it is necessary to identify which projection measurements are defective. This can be accomplished by performing a preliminary reconstruction of the projection data using known reconstruction techniques, such as filtered back projection. The preliminary image can be displayed on a cathode ray tube (CRT). The starburst artifacts will be obvious to a user, since they appear as high-density regions having streaks and other shading artifacts which originate from the regions in the image where the high-density object are centered. These regions can be identified by using a light pen (similar to that described in the afore-identified U.S. Pat. No. 4,075,700) to draw a boundary around the image of the object. Alternatively, a geometrical region of interest (ROI), such as a circle, can be positioned around the object using a trackball control feature commonly available in modern CT scanners. For example, U.S. Pat. No. 4,245,244, assigned to the same assignee as the present invention, discloses and claims a device for delineating zones in a video image display under the control of a trackball. Another example of a cursor generator for use in computerized tomography and other image display systems is disclosed and claimed in U.S. Pat. No. 4,259,725, which is also assigned to the same assignee as the present application.
Once the high density objects present in the preliminary image are outlined in the manner described above, well-known procedures can be used to determine which projection measurements correspond to readings through the object. For a given computerized tomography scanner geometry (e.g., source-to-isocenter distance, source-to-detector distance, the fan angle of the X-ray beam, and the number of detectors in the detector array), it is possible to determine which projection measurements in each projection contributed to the shadow of the object on the detector array of the high-density object. If there are multiple regions of interest defined, indicating the presence of more than one high-density object, then the detector measurements contributing to each region can be independently identified.
It will be beneficial to consider some additional prior art methods of producing a corrected image given the fact that some of the projection measurements are unusable and, therefore, may be considered as missing. This is important because widely used filtered back projection algorithms for reconstructing CT images will not work satisfactorily because of the requirement that all of the projection data be available. Mathematically, it is well known that if some fraction of the projection data is available, then all of the projection data can be calculated. This can be accomplished because of the consistency of the Radon transform of the object. However, methods relying on this principle are extremely computationally expensive and unstable when any noise is present.
Another known method to reconstruct the partial projection data is to use iterative reconstruction methods. These methods are known as algebraic reconstruction techniques and are frequently referred to as ART. The advantage of the ART methods over filtered back projection is that they can work reasonably well with partial projection data and, hence, can be used to remove artifacts. It is believed that ART is a highly effective reconstruction method for removing artifacts in situations where some of the projection data is corrupted and cannot be used. However, a drawback of ART is that it is extremely computationally expensive and unlike filtered back projection difficult to implement in high-speed form, requiring special-purpose hardward to implement the reconstruction algorithm.
It is therefore apparent that it is desirable to obtain a computationally inexpensive algorithm for the purpose of removing artifacts from images containing high-density objects. One of the preferred methods would be to use filtered back projection in the reconstruction process due to the fact that many of the commercially available computerized tomography scanners have hardware to support this method. The filtered backprojection method requires, however, that all of the projection measurements be available.
U.S. Pat. No. 4,178,510 relates to the use of filtered back projection reconstruction methods for constructing an image when one or more detectors in the detector array are not operational and therefore the data therefrom is unusable and must be replaced. In accordance with this method, the readings corresponding to the inoperative detectors can be obtained by interpolation of data from valid detector readings on either side of the inoperational detectors, enabling the repair of such detectors to be performed at a later, more convenient time. The interpolation used can be either linear interpolation or higher order. Higher order interpolation is also frequently referred to as polynominal completion.
The method described in the aforeidentified patent has similarities to techniques used for artifact removal. In one situation, the projection data is missing because the detectors are inoperative, while in the other situation the detectors are operative but the data is unusable (and therefore may be considered as missing or unavailable). It will be apparent to those skilled in the art that in the situation of artifact removal simple interpolation can be used to remove the unusable data. A difference between the two situations, however, is that in the inoperative detector case the same detectors are inoperative in every projection. In the artifact removal case, the detectors which sense the unusable data will change from view to view as the X-ray source and detector rotate about the object being imaged. In the latter situation, the actual projection measurements, which are corrupted and must be replaced, can be determined by using the region-of-interest feature described hereinabove. This method shall hereinafter be referred to as simple polynomial completion algorithm. A difficulty which arises with the simple polynomial completion algorithm is that when other high-density objects are in the field of view (FOV), such as bone associated with the spinal column, streak artifacts will be generated in the region of the corrected image between the position where the removed object was and the other high-density objects present in the image.
The paper entitled "An Algorithm for the Reduction of Metal Clip Artifacts in CT Reconstruction," in Medical Physics, Vol. 8, November/December (1981), pp 789-807, G. Glover and N. Pelc, presents an improved method which reduces some of the induced streak artifacts. This method utilizes local averages of the projection data (after the object to be removed is mathematically centered at the isocenter of the system) to increase the object-to-background ratio. This process, in effect, creates a base on which to do the linear interpolation. This method is known as the rubout algorithm for artifact removal. An improvement of the rubout algorithm for removing artifacts due to objects with extremely high density is also disclosed in the above-identified article. In this method, reprojections of the other high-density objects in the field of view are subtracted from the original, unmodified projection set before the application of the rubout algorithm. The rubout algorithm is disclosed and claimed in commonly assigned U.S. patent application Ser. No. 335,973, filed Dec. 30, 1981.
Some of the aforementioned artifact removal methods do not work satisfactorily when multiple high-density objects are present in the field of view (FOV) and need to be removed. The previous methods were applied sequentially on the multiple objects to be removed and failed for this reason, as will be more fully disclosed hereinafter.
In view of the foregoing, it is a general object of the present invention to improve the quality of this class of CT images by minimizing the effect of image artifacts created by multiple high density objects located in the field of view.
Another object of the prsent invention is to reduce artifacts caused by the presence of multiple, sharp, localized discontinuities, such as surgical clips in the field of view without degrading the CT image by introducing other artifacts.
A further object of the present invention is to reduce artifacts caused by the presence of multiple high-density objects, such as prostheses and dental fillings, without resorting to computationally expensive reconstruction algorithms.